Gemini 3.1 Pro Preview (batch) vs Gemini 2.5 Pro (batch)
Both sit behind the same key and the same code on uttapen — the only thing that changes is the model string, so you can run each of them against your own workload without touching anything else. On cost, Gemini 2.5 Pro (batch) comes out about 1.2× cheaper.
| Feature |  Gemini 3.1 Pro Preview (batch) | Gemini 2.5 Pro (batch) |
|---|---|---|
| Provider | ||
| Model id | google/gemini-3.1-pro-preview:batch | google/gemini-2.5-pro:batch |
| Context | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 65,536 tokens | 65,536 tokens |
| Input / 1M tokens | 290,125 toman | 181,328 toman |
| Output / 1M tokens | 1,740,750 toman | 1,450,625 toman |
| ≈ one 1,000-word request | 2,640 toman | 2,122 toman |
| Input caching | No | 36,266 toman / 1M |
| Image input | Yes | Yes |
| File input | Yes | Yes |
| Tool calling | Yes | Yes |
| JSON output | Yes | Yes |
| Reasoning mode | Yes | Yes |
Which one for what?
Gemini 3.1 Pro Preview (batch)
- Multi-step problems, maths, and tracking down a bug
- Whole documents or a codebase in a single request
- Reading screenshots, invoices, and scanned forms
- Agents that call your own APIs and database
2,640 toman per 1,000 words · Model page
Gemini 2.5 Pro (batch)
- Multi-step problems, maths, and tracking down a bug
- Whole documents or a codebase in a single request
- Reading screenshots, invoices, and scanned forms
- Agents that call your own APIs and database
2,122 toman per 1,000 words · Model page
Run both with the same code
Swap the model value between the two ids and send the same request twice; what each answer cost comes back in the X-Uttapen-Cost-Toman header.
curl https://api.uttapen.ir/v1/chat/completions \
-H "Authorization: Bearer sk-up-…" \
-H "Content-Type: application/json" \
-d '{
"model": "google/gemini-3.1-pro-preview:batch",
"messages": [{"role": "user", "content": "Introduce yourself in one sentence."}],
"stream": true
}'from openai import OpenAI
client = OpenAI(
base_url="https://api.uttapen.ir/v1",
api_key="sk-up-…",
)
stream = client.chat.completions.create(
model="google/gemini-3.1-pro-preview:batch",
messages=[{"role": "user", "content": "Introduce yourself in one sentence."}],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.uttapen.ir/v1",
apiKey: "sk-up-…",
});
const stream = await client.chat.completions.create({
model: "google/gemini-3.1-pro-preview:batch",
messages: [{ role: "user", content: "Introduce yourself in one sentence." }],
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}<?php
// composer require openai-php/client guzzlehttp/guzzle
$client = OpenAI::factory()
->withBaseUri('https://api.uttapen.ir/v1')
->withApiKey('sk-up-…')
->make();
$result = $client->chat()->create([
'model' => 'google/gemini-3.1-pro-preview:batch',
'messages' => [['role' => 'user', 'content' => 'Introduce yourself in one sentence.']],
]);
echo $result->choices[0]->message->content;package main
import (
"context"
"fmt"
"github.com/openai/openai-go"
"github.com/openai/openai-go/option"
)
func main() {
client := openai.NewClient(
option.WithBaseURL("https://api.uttapen.ir/v1"),
option.WithAPIKey("sk-up-…"),
)
resp, err := client.Chat.Completions.New(context.Background(), openai.ChatCompletionNewParams{
Model: "google/gemini-3.1-pro-preview:batch",
Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
})
if err != nil {
panic(err)
}
fmt.Println(resp.Choices[0].Message.Content)
}model = "google/gemini-2.5-pro:batch"
More comparisons: all pairs · model rankings · full catalogue
base_url = https://api.uttapen.ir/v1